Department of Infectious Diseases, Nanjing Lishui People's Hospital, Zhongda Hospital Lishui Branch, Southeast University, No.86, Chongwen Street, Lishui District, Nanjing City, 211002, China.
Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
BMC Genomics. 2023 Jul 1;24(1):368. doi: 10.1186/s12864-023-09491-2.
Cell death plays a crucial role in the progression of active tuberculosis (ATB) from latent infection (LTBI). Cuproptosis, a novel programmed cell death, has been reported to be associated with the pathology of various diseases. We aimed to identify cuproptosis-related molecular subtypes as biomarkers for distinguishing ATB from LTBI in pediatric patients.
The expression profiles of cuproptosis regulators and immune characteristics in pediatric patients with ATB and LTBI were analyzed based on GSE39939 downloaded from the Gene Expression Omnibus. From the 52 ATB samples, we investigated the molecular subtypes based on differentially expressed cuproptosis-related genes (DE-CRGs) via consensus clustering and related immune cell infiltration. Subtype-specific differentially expressed genes (DEGs) were found using the weighted gene co-expression network analysis. The optimum machine model was then determined by comparing the performance of the eXtreme Gradient Boost (XGB), the random forest model (RF), the general linear model (GLM), and the support vector machine model (SVM). Nomogram and test datasets (GSE39940) were used to verify the prediction accuracy.
Nine DE-CRGs (NFE2L2, NLRP3, FDX1, LIPT1, PDHB, MTF1, GLS, DBT, and DLST) associated with active immune responses were ascertained between ATB and LTBI patients. Two cuproptosis-related molecular subtypes were defined in ATB pediatrics. Single sample gene set enrichment analysis suggested that compared with Subtype 2, Subtype 1 was characterized by decreased lymphocytes and increased inflammatory activation. Gene set variation analysis showed that cluster-specific DEGs in Subtype 1 were closely associated with immune and inflammation responses and energy and amino acids metabolism. The SVM model exhibited the best discriminative performance with a higher area under the curve (AUC = 0.983) and relatively lower root mean square and residual error. A final 5-gene-based (MAN1C1, DKFZP434N035, SIRT4, BPGM, and APBA2) SVM model was created, demonstrating satisfactory performance in the test datasets (AUC = 0.905). The decision curve analysis and nomogram calibration curve also revealed the accuracy of differentiating ATB from LTBI in children.
Our study suggested that cuproptosis might be associated with the immunopathology of Mycobacterium tuberculosis infection in children. Additionally, we built a satisfactory prediction model to assess the cuproptosis subtype risk in ATB, which can be used as a reliable biomarker for the distinguishment between pediatric ATB and LTBI.
细胞死亡在从潜伏性结核感染（LTBI）向活动性结核病（ATB）的进展中起着关键作用。细胞铜死亡是一种新的程序性细胞死亡，已被报道与各种疾病的病理有关。我们旨在确定与小儿 ATB 和 LTBI 鉴别相关的铜死亡相关分子亚型作为生物标志物。
基于从基因表达综合数据库（GEO）下载的 GSE39939，分析小儿 ATB 和 LTBI 患者的铜死亡调节因子表达谱和免疫特征。在 52 例 ATB 样本中，我们通过一致性聚类和相关免疫细胞浸润，基于差异表达的铜死亡相关基因（DE-CRGs）研究了分子亚型。使用加权基因共表达网络分析发现了特定于亚型的差异表达基因（DEGs）。通过比较 eXtreme Gradient Boost（XGB）、随机森林模型（RF）、广义线性模型（GLM）和支持向量机模型（SVM）的性能，确定了最佳的机器模型。使用 Nomogram 和测试数据集（GSE39940）验证预测准确性。
在 ATB 和 LTBI 患者之间确定了 9 个与活性免疫反应相关的差异表达铜死亡调节因子（NFE2L2、NLRP3、FDX1、LIPT1、PDHB、MTF1、GLS、DBT 和 DLST）。在 ATB 儿科中确定了两种铜死亡相关的分子亚型。单样本基因集富集分析表明，与亚型 2 相比，亚型 1的特点是淋巴细胞减少和炎症激活增加。基因集变异分析表明，亚型 1 中簇特异性的 DEGs 与免疫和炎症反应以及能量和氨基酸代谢密切相关。SVM 模型表现出最佳的判别性能，具有较高的曲线下面积（AUC=0.983）和相对较低的均方根和残差。建立了一个最终基于 5 个基因的 SVM 模型（MAN1C1、DKFZP434N035、SIRT4、BPGM 和 APBA2），在测试数据集（AUC=0.905）中表现出令人满意的性能。决策曲线分析和 Nomogram 校准曲线也表明了该模型在区分儿童 ATB 和 LTBI 中的准确性。
我们的研究表明，铜死亡可能与儿童结核分枝杆菌感染的免疫病理学有关。此外，我们构建了一个满意的预测模型来评估 ATB 中的铜死亡亚型风险，该模型可作为区分小儿 ATB 和 LTBI 的可靠生物标志物。
